імітаційне моделювання

Manufactured laboratory samples of new rod external fixation devices (REFD) human bone fragments with the joint design made of biocompatible composite materials. Experimental testing and calculation and theoretical study of REFD rod joints of new design for osteosynthesis damaged human limbs. The developed osteosynthesis designs samples are tested in medical institutions of Ukraine for quality treatment of damaged bone fractures.

Work is devoted creation of theoretical baseline for working out and research of principles and methods of raise of capacity (ПС) for microwave broadband radio access systems (СШР) by use of production engineering of adaptive existential machining of signals МІМО (Multiple Input Multiple Output).

The new link adaptation method was created based on multicriteria channel state estimates with fuzzy logic mathematical apparatus. Matching link adaptation algorithms were created with usage of unusual improved fuzzy inference algorithm based on both link state energy estimations and multicriteria estimations (energetical, probabilistical, and statistical). The rules of membership function construction were determined. They are constructed by direct methods based on simulation results or laboratory measurements of stationary channel immunity.

1. State registration number of the theme - 0112U003164, NTUU "KPI" - 2523-p.
2. Supervisor - prof. Pankratova Nataliya D.
3. The essence of development, the main results.

Developed some of methods for solving ill-structed problems for modeling, prediction and classification. All methods use Bayesian networks. Proposed a new five step method for finding the parameters of Bayesian networks with hidden nodes. Method bases on an expectation maximization algorithm. Suggested Pearson's, Chuprov's, Cramer's, Goodman's and mutual information coefficients for finding interconnections between Bayesian network's nodes. For solving the problem of modeling the behavior of complex systems proposed original method for construction and application hybrid Bayesian networks.